Samenvatting
Imitation learning is a promising route to instruct robotic multi-agent systems. However, imitating agents should be able to decide autonomously what behavior, observed in others, is interesting to copy. Here we investigate whether a simple recurrent network (Elman Net) can be used to extract meaningful chunks from a continuous sequence of observed actions. Results suggest that, even in spite of the high level of task specific noise, Elman nets can be used for isolating re-occurring action patterns in robots. Limitations and future directions are discussed.
Originele taal-2 | Engels |
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Titel | Artificial Intelligence and Soft Computing - ICAISC 2008 - 9th International Conference, Zakopane, Poland, June 22-26. Proceedings |
Redacteuren | L. Rutkowski, R. Tadeusiewicz, L.A. Zadeh, J.M. Zurada |
Pagina's | 1198-1209 |
Aantal pagina's | 12 |
DOI's | |
Status | Gepubliceerd - 4 aug. 2008 |
Evenement | 9th International conference on Artificial Intelligence and Soft Computing (ICAISC 2008) - Zakopane, Polen Duur: 22 jun. 2008 → 26 jun. 2008 Congresnummer: 9 |
Publicatie series
Naam | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 5097 LNAI |
ISSN van geprinte versie | 0302-9743 |
ISSN van elektronische versie | 1611-3349 |
Congres
Congres | 9th International conference on Artificial Intelligence and Soft Computing (ICAISC 2008) |
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Verkorte titel | ICAISC 2008 |
Land/Regio | Polen |
Stad | Zakopane |
Periode | 22/06/08 → 26/06/08 |
Ander | ICAISC 2008: Artificial Intelligence and Soft Computing ; 9th International conference, Zakopane, Poland, June 22-26 2008 |